Intermediate Probability: A Computational Approach

Description

Intermediate Probability is the natural extension of the author's Fundamental Probability. It details several highly important topics, from standard ones such as order statistics, multivariate normal, and convergence concepts, to more advanced ones which are usually not addressed at this mathematical level, or have never previously appeared in textbook form. The author adopts a computational approach throughout, allowing the reader to directly implement the methods, thus greatly enhancing the learning experience and clearly illustrating the applicability, strengths, and weaknesses of the theory.

A whole chapter is dedicated to nesting, generalizing, and asymmetric extensions of popular distributions, as have become popular in empirical finance and other applications.

Provides all essential programming code in Matlab and R.

The user-friendly style of writing and attention to detail means that self-study is easily possible, making the book ideal for senior undergraduate and graduate students of mathematics, statistics, econometrics, finance, insurance, and computer science, as well as researchers and professional statisticians working in these fields.

"I thoroughly enjoyed Intermediate Probability. I was so thrilled with it that I have shared it with some of my colleagues. They have called it a 'gold mine' of problems and resources, and describing it as 'amazing.' ... I highly recommend it." (Journal of the American Statistical Association, September 2009)

"The reader-friendly style of the text itself would make the book appropriate for self-study or classroom adoption." (MAA Reviews, December 2007)